plotly 入門

郭耀仁

2017-12-04

準備事項

安裝與載入

install.packages("plotly")
install.packages("gapminder")
install.pacakges("tidyverser")
library(plotly)
library(gapminder)
library(tidyverse)

目的

  • 製作具有互動元件的圖表
  • 讓使用者可以略過 JavaScript
  • 讓使用者繼續使用 R

gapminder 資料

還記得 Hans Rosling 的 The best stats you’ve ever seen 嗎？

dim(gapminder)
## [1] 1704    6
head(gapminder)
## # A tibble: 6 x 6
##       country continent  year lifeExp      pop gdpPercap
##        <fctr>    <fctr> <int>   <dbl>    <int>     <dbl>
## 1 Afghanistan      Asia  1952  28.801  8425333  779.4453
## 2 Afghanistan      Asia  1957  30.332  9240934  820.8530
## 3 Afghanistan      Asia  1962  31.997 10267083  853.1007
## 4 Afghanistan      Asia  1967  34.020 11537966  836.1971
## 5 Afghanistan      Asia  1972  36.088 13079460  739.9811
## 6 Afghanistan      Asia  1977  38.438 14880372  786.1134

繪製分配的圖形

直方圖

gapminder_2007 <- gapminder %>%
  filter(year == 2007)
p <- plot_ly(data = gapminder_2007, x = ~gdpPercap, type = "histogram")

顯示直方圖

p

盒鬚圖

p <- plot_ly(data = gapminder_2007, x = ~continent, y = ~lifeExp, color = ~continent, type = "box")

顯示盒鬚圖

p

繪製相關的圖形

散佈圖

p <- plot_ly(data = gapminder_2007, x = ~gdpPercap, y = ~lifeExp, color = ~continent, type = "scatter", mode = "markers")

顯示散佈圖

p

繪製排名的圖形

長條圖

north_asia <- gapminder_2007 %>%
  filter(country %in% c("China", "Taiwan", "Japan", "Korea, Rep."))
north_asia$country <- as.character(north_asia$country)
p <- plot_ly(data = north_asia, x = ~country, y = ~gdpPercap, type = "bar", color = ~country)

顯示長條圖

p

繪製時間序列的圖形

線圖

twn <- gapminder %>%
  filter(country == "Taiwan")
p <- plot_ly(data = twn, x = ~year, y = ~lifeExp, type = "scatter", mode = "lines")

顯示線圖

p

切割畫布

準備資料

north_asia <- gapminder %>%
  filter(country %in% c("China", "Taiwan", "Japan", "Korea, Rep."))
north_asia$country <- as.character(north_asia$country)
p1 <- north_asia %>%
  filter(country == "Japan") %>%
  plot_ly(x = ~year, y = ~gdpPercap,  type = "scatter", mode = "lines") %>%
  add_lines(name = ~"Japan")
p2 <- north_asia %>%
  filter(country == "Korea, Rep.") %>%
  plot_ly(x = ~year, y = ~gdpPercap,  type = "scatter", mode = "lines") %>%
  add_lines(name = ~"Korea, Rep.")

subplot 函數

subplot(p1, p2)

實作簡易版的 Hans Rosling: The best stats you’ve ever seen

1952 年的氣泡圖

gapminder_1952 <- gapminder %>%
  filter(year == 1952)
bubble_1952 <- gapminder_1952 %>% 
  plot_ly(x = ~gdpPercap, y = ~lifeExp, color = ~continent, size = ~pop, type = "scatter", mode = "markers",  sizes = c(10, 1000), text = ~country)
bubble_1952

將 X 軸改為 log scale

bubble_1952_log <- gapminder_1952 %>% 
  plot_ly(x = ~gdpPercap, y = ~lifeExp, color = ~continent, size = ~pop, type = "scatter", mode = "markers",  sizes = c(10, 1000), text = ~country) %>%
  layout(xaxis = list(type = "log"))
bubble_1952_log

繪製所有年份的氣泡圖

新增 frame = ~year 參數

bubble_chart <- gapminder %>% 
  plot_ly(x = ~gdpPercap, y = ~lifeExp, color = ~continent, size = ~pop, type = "scatter", mode = "markers", sizes = c(10, 1000), text = ~country, frame = ~year) %>%
  layout(title = "Gapminder Data Visualization",
         xaxis = list(title = "GDP Per Capita", type = "log"),
         yaxis = list(title = "Life Expectancy"))
bubble_chart